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 | | Engineering Optimization: Theory and Practice, 3rd Edition by Singiresu S. Rao ISBN-10: 9780471550341 ISBN-10: 0-471-55034-5 ISBN-13: 9780471550341 ISBN-13: 978-0-471-55034-1 Hardcover 1996-02-15 Wiley-Interscience Find Lowest Price |
Editorials | ||
Product Description A rigorous mathematical approach to identifying a set of design alternatives and selecting the best candidate from within that set, engineering optimization was developed as a means of helping engineers to design systems that are both more efficient and less expensive and to develop new ways of improving the performance of existing systems. Thanks to the breathtaking growth in computer technology that has occurred over the past decade, optimization techniques can now be used to find creative solutions to larger, more complex problems than ever before. As a consequence, optimization is now viewed as an indispensable tool of the trade for engineers working in many different industries, especially the aerospace, automotive, chemical, electrical, and manufacturing industries. In Engineering Optimization, Professor Singiresu S. Rao provides an application-oriented presentation of the full array of classical and newly developed optimization techniques now being used by engineers in a wide range of industries. Essential proofs and explanations of the various techniques are given in a straightforward, user-friendly manner, and each method is copiously illustrated with real-world examples that demonstrate how to maximize desired benefits while minimizing negative aspects of project design. Comprehensive, authoritative, up-to-date, Engineering Optimization provides in-depth coverage of linear and nonlinear programming, dynamic programming, integer programming, and stochastic programming techniques as well as several breakthrough methods, including genetic algorithms, simulated annealing, and neural network-based and fuzzy optimization techniques. Designed to function equally well as either a professional reference or a graduate-level text, Engineering Optimization features many solved problems taken from several engineering fields, as well as review questions, important figures, and helpful references. An indispensable working resource for practicing engineers Engineering Optimization Providing engineers with a rigorous, systematic method for rapidly zeroing in on the most innovative, cost-effective solutions to some of today's most challenging engineering design problems, optimization is a powerful tool of the trade for engineers in virtually every discipline. Now, in his latest book, Engineering Optimization, Singiresu S. Rao provides you with the most practical, up-to-date, and comprehensive coverage of new and classical optimization techniques currently in use throughout a wide range of industries. Designed to serve as both a daily working resource and an excellent graduate-level text, Engineering Optimization gives you: * In-depth coverage of linear and nonlinear programming, dynamic programming, integer programming, and stochastic programming techniques * New or recently developed methods, including genetic algorithms, simulated annealing, neural network-based and fuzzy optimization techniques * Dozens of real-world design optimization examples taken from a wide range of industries * Numerous solved problems and review questions * An extensive bibliography Engineering Optimization is a valuable working resource for engineers employed in practically all technological industries. It is also a superior didactic tool for graduate students of mechanical, civil, electrical, chemical, and aerospace engineering. | ||
Reviews | ||
Great introductory text for engineers! This work is one of my favorite all-around optimization books. It covers a lot of ground and it is very well written from a pedegogical point of view. Covered are a full range of linear and nonlinear methods, and for both constrained and unconstrained problem types. Also treated are geometric, dynamic, and integer programming techniques. Many of the algorithms within the book are presented with step-by-step examples which greatly assist the reader. One downside is that I found the explanations of SQP and GRG methods to be confusing and insufficient. As these two techniques are among the more efficient and robust for many NLP problems (which are essential for engineering applications), this was disappointing. I hope Professor Rao will write a fourth edition with improvements in these particular areas. Otherwise, this book stands out as a useful and practical reference for both students and practicing engineers. If I had to have only one general book on optimization, this would be it. Other useful favorites are "Numerical Optimization" by Nocedal and Wright, "Practical Methods of Optimization" by Fletcher, and "Numerical Methods for Unconstrained Optimization and Nonlinear Equations" by Dennis and Schnabel. | ||
An update to the review above Since writing the above review in 1999, I have become familiar with some of the more recent methods for linear optimization. If you are interested in linear/integer optimization, you may be interested to know that this book discusses the simplex method and its derivatives, and describes Gomory cutting plane method for integer programming. Lest you get carried away by the unbridled optimism expressed in the previous review , please note - this book does not cover iterative linear programming methods such as interior point methods, EXCEPT for a rather good, detailed description of Karmarkar's 1984 method (projective transformation), with a numerical example. Another omission is trust-region methods; however line-search methods are discussed. So if 0/1 optimization, interior point methods, semi-definite programming, trust-region methods is your cup of tea, shop elsewhere. I'm rolling back my previous rating from 5-stars to 4-stars on this count. | ||
A most valued addition to my bookshelf. I am a sucker for books on applied mathematics. This book ranks among my most valued ones, and is always within constant reach for reference on optimization algorithms. The book covers linear programming, nonlinear programming, geometric programming, dynamic programming, integer programming, and stochastic programming. A wide array of methods which seem impressively complete are covered in this 903-page book. The addressing of the topics is geared more towards making the reader understand how the algorithms were derived (which is welcome, in contrast to chasing up the original research papers), and using them. Just about every method is illustrated clearly with examples - a welcome feature of the book. One minor drawback is that all examples and exercises that are applied to engineering, are drawn from mechanical and civil areas (note: there are also many examples that are mathematical toy problems). Having said that, I must hasten to add that I am an electrical engineer, and I have no problem at all in using this book. Strongly recommended for people who work with optimization algorithms! | ||